Creative Fatigue Detector for Paid Media Campaigns
Advertising & Paid MediaadvancedClaude 3.5 Sonnet or GPT-4o. Claude excels at structured analysis and can handle complex data interpretation with clear reasoning. GPT-4o offers faster processing for large datasets. Both handle multi-step analytical frameworks well. For real-time campaign data integration, GPT-4o's API performance is slightly superior.
When to Use This Prompt
Use this prompt when your paid media campaigns show declining performance despite stable or increased spending, or when you're running the same creatives for 4+ weeks and want to proactively detect fatigue before it impacts ROI. Essential for managing large-scale campaigns across multiple platforms where creative rotation is critical to maintaining efficiency.
The Prompt
You are a performance marketing analyst specializing in creative fatigue detection. Analyze the following paid media campaign data to identify creative fatigue signals and recommend refresh strategies.
## Campaign Data to Analyze
Provide the following metrics for [CAMPAIGN_NAME] across [DATE_RANGE]:
- Daily/weekly impressions, clicks, and CTR trends
- Cost per click (CPC) and cost per conversion (CPA) trends
- Conversion rate by creative variant
- Frequency data (average impressions per user)
- Creative performance by platform: [PLATFORM_LIST]
- Historical performance baseline from [BASELINE_PERIOD]
- Budget allocation across [NUMBER_OF_CREATIVES] creative variants
- Audience segment performance (if available)
## Analysis Framework
Evaluate creative fatigue using these indicators:
1. **Performance Degradation**: Compare current metrics to baseline. Flag any CTR decline >15%, CPA increase >20%, or conversion rate drop >10% over the analysis period.
2. **Frequency Saturation**: Identify if average frequency exceeds [FREQUENCY_THRESHOLD]. High frequency + declining CTR = fatigue signal.
3. **Engagement Decay Pattern**: Look for consistent downward trends in CTR/conversion rate despite stable or increased spend. Distinguish from seasonal patterns.
4. **Platform-Specific Signals**: Analyze if fatigue is platform-wide or isolated to [SPECIFIC_PLATFORM]. Mobile vs. desktop performance divergence.
5. **Audience Segment Analysis**: Determine if fatigue affects all segments equally or concentrates in specific demographics/behaviors.
## Output Requirements
Provide a structured fatigue assessment:
**Fatigue Level**: Rate as None, Mild, Moderate, or Severe with confidence score (0-100%).
**Key Indicators**: List the 3-5 strongest fatigue signals with specific data points.
**Timeline**: Estimate when fatigue began and current trajectory.
**Affected Elements**: Identify which creatives, audiences, or platforms show strongest fatigue.
**Recommended Actions**: Provide 4-6 specific refresh recommendations prioritized by impact potential, including:
- Creative refresh strategy (new messaging angles, visual styles, formats)
- Audience expansion or segmentation adjustments
- Frequency capping recommendations
- A/B testing framework for new creatives
- Timing for creative rotation
**Success Metrics**: Define KPIs to track if refresh strategy works (e.g., "CTR should recover to X% within Y days").
Be specific with numbers and avoid generic advice. Reference the actual data provided.
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Tips for Best Results
- 1.Provide actual campaign data in CSV or table format rather than summaries. AI performs better with raw numbers and can spot patterns humans miss in large datasets.
- 2.Include historical baseline data (previous 3-6 months) so the AI can distinguish fatigue from seasonal trends or platform algorithm changes.
- 3.Specify your industry and audience type (e.g., 'B2B SaaS, IT decision-makers') so recommendations account for typical fatigue patterns in your vertical.
- 4.Ask the AI to flag which metrics are most actionable for your specific goals—some teams prioritize CTR, others CPA or ROAS, which changes fatigue interpretation.
Example Output
## Creative Fatigue Assessment: Q4 Holiday Campaign
**Fatigue Level**: Moderate (72% confidence)
**Key Indicators**:
1. CTR declined 18% week-over-week (3.2% → 2.6%) despite 12% budget increase
2. CPA increased 24% over 4-week period ($18.50 → $23.00)
3. Average frequency reached 8.2 impressions/user; CTR drops 0.3% per frequency increment above 6
4. Facebook performance degraded 22% while Google Ads stable, suggesting platform-specific saturation
5. 25-34 age segment shows 31% CPA increase; 18-24 segment stable
**Timeline**: Fatigue signals emerged Week 3 of campaign (Dec 8), accelerating in Week 4. Current trajectory suggests Severe fatigue within 7 days without intervention.
**Affected Elements**: Primary creative (carousel ad with product showcase) shows strongest fatigue. Secondary creative (lifestyle video) maintains 2.8% CTR. Facebook audience saturation evident; Instagram audience still performing.
**Recommended Actions**:
1. **Immediate**: Pause primary creative, increase budget allocation to secondary creative by 40% (projected 15-20% CPA improvement)
2. **This Week**: Launch 3 new creative variants testing different value propositions (free shipping, limited time, social proof angles)
3. **Frequency Management**: Implement 5-impression daily frequency cap for 25-34 segment; maintain 8 for 18-24
4. **Audience Expansion**: Expand lookalike audience from 1% to 3% similarity to reach fresh prospects
5. **Platform Shift**: Reallocate 20% of Facebook budget to Google Shopping to diversify exposure
6. **Testing**: A/B test new creatives against secondary creative for 48 hours before full rollout
**Success Metrics**: Expect CTR recovery to 2.9%+ and CPA reduction to $20 within 5 days of creative refresh. Monitor frequency decline to 6.5 impressions/user.
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Courses, workshops, frameworks, daily intelligence, and 6 proprietary tools — built for marketing leaders adopting AI.
Trusted by 10,000+ Directors and CMOs.